Use of CBL exon 8 and 9 mutations in diagnosis of myeloproliferative neoplasms and myelodysplastic/myeloproliferative disorders: an analysis of 636 cases.

We analyzed 636 patients with diverse myeloproliferative neoplasms or myelodysplastic/myeloproliferative neoplasms for mutations of the Casitas B-cell lymphoma gene (CBL(mut)) in exons 8 and 9 and performed correlations to other genetic alterations. CBL(mut) were detected in 63 of 636 (9.9%) of these selected patients. CBL(mut) were more frequent in myelodysplastic/myeloproliferative neoplasms than myeloproliferative neoplasms (51 of 328, 15.5% vs. 12 of 291, 4.1%; P<0.001). Frequency was 48 of 278 (17.3%) in chronic myelomonocytic leukemia and 3 of 33 (9.1%) in unclassifiable myelodysplastic/myeloproliferative neoplasms. CBL(mut) was not detected in polycythemia vera, primary myelofibrosis, essential thrombocythemia, or refractory anemia with ring sideroblasts and marked thrombocytosis. CBL(mut) were underrepresented in JAK2(V617F) mutated as compared to JAK2V617(wt) cases (P<0.001), and mutually exclusive of JAK2exon12(mut) and MPLW515(mut). CBL(mut) were associated with monosomy 7 (P=0.008) and TET2(mut) (P=0.003). In chronic myelomonocytic leukemia, CBL(mut) had no significant impact on survival outcomes. Therefore, CBL(mut) are frequent in chronic myelomonocytic leukemia, absent in classical myeloproliferative neoplasms, and are only exceptionally found in coincidence with JAK-STAT pathway activating mutations.

Multilineage dysplasia does not influence prognosis in CEBPA-mutated AML, supporting the WHO proposal to classify these patients as a unique entity.

In 2008, the World Health Organization introduced CEBPA (encoding the CCAAT/enhancer binding protein)-mutated acute myeloid leukemia (AML) as a provisional entity. However, the classification of CEBPA-mutated AML with multilineage dysplasia (MLD; ≥ 50% dysplastic cells in 2-3 lineages) remains to be clarified. In the present study, we investigated 108 CEBPA-mutated AML patients for the impact of MLD, karyotype, and additional mutations. MLD(+) patients differed from MLD(-) patients only by lower mean WBC counts, not by biologic characteristics, cytogenetic risk profiles, or additional mutations. Survival was better for female patients, patients < 60 years of age, for intermediate versus adverse karyotypes, and, in the case of FLT3-ITD negativity, biallelic versus monoallelic/homozygous CEBPA mutations. In contrast, 2-year overall survival and event-free survival did not differ significantly between MLD(+) and MLD(-) patients. By univariable Cox regression analysis, sex, age, WBC count, and cytogenetic risk category were related to overall survival, but MLD was not. Therefore, because dysplasia is not relevant for this subtype, CEBPA-mutated AML patients should be characterized only according to mutation status, cytogenetic risk group, or additional mutations.

PhenomiR: microRNAs in human diseases and biological processes.

The association of dysregulated microRNAs (miRNAs) and diseases has been shown in a variety of studies. Here, we review a resource denoted as PhenomiR, providing systematic and comprehensive access to such studies. It allows machine-readable access to miRNA and target relations from these studies to study the impact of miRNAs on multifactorial diseases across many samples and biological replicates. We summarize the PhenomiR data structure and its content and show how to access the database and use it in everyday miRNA profile analysis using the R language.

MicroRNAs coordinately regulate protein complexes.

BACKGROUND: In animals, microRNAs (miRNAs) regulate the protein synthesis of their target messenger RNAs (mRNAs) by either translational repression or deadenylation. miRNAs are frequently found to be co-expressed in different tissues and cell types, while some form polycistronic clusters on genomes. Interactions between targets of co-expressed miRNAs (including miRNA clusters) have not yet been systematically investigated. RESULTS: Here we integrated information from predicted and experimentally verified miRNA targets to characterize protein complex networks regulated by human miRNAs. We found striking evidence that individual miRNAs or co-expressed miRNAs frequently target several components of protein complexes. We experimentally verified that the miR-141-200c cluster targets different components of the CtBP/ZEB complex, suggesting a potential orchestrated regulation in epithelial to mesenchymal transition. CONCLUSIONS: Our findings indicate a coordinate posttranscriptional regulation of protein complexes by miRNAs. These provide a sound basis for designing experiments to study miRNA function at a systems level.

Screening for NPHS2 mutations may help predict FSGS recurrence after transplantation.

Steroid-resistant focal segmental glomerulosclerosis (FSGS) often recurs after renal transplantation. In this international survey, we sought to identify genotype-phenotype correlations of recurrent FSGS. We surveyed 83 patients with childhood-onset primary FSGS who received at least one renal allograft and analyzed 53 of these patients for NPHS2 mutations. The mean age at diagnosis was 6.7 years, and the mean age at first renal transplantation was 13 years. FSGS recurred in 30 patients (36%) after a median of 13 days (range, 1.5 to 152 days). Twenty-three patients received a second kidney transplant, and FSGS recurred in 11 (48%) after a median of 16 days (range, 2.7 to 66 days). None of the 11 patients with homozygous or compound heterozygous NPHS2 mutations developed recurrent FSGS compared with 45% of patients without mutations. These data suggest that genetic testing for pathogenic mutations may be important for prognosis and treatment of FSGS both before and after transplantation.

miTALOS: analyzing the tissue-specific regulation of signaling pathways by human and mouse microRNAs.

MicroRNAs (miRNAs) are an important class of post-transcriptional regulators of gene expression that are involved in various cellular and phenotypic processes. A number of studies have shown that miRNA expression is induced by signaling pathways. Moreover, miRNAs emerge as regulators of signaling pathways. Here, we present the miTALOS web resource, which provides insight into miRNA-mediated regulation of signaling pathways. As a novel feature, miTALOS considers the tissue-specific expression signatures of miRNAs and target transcripts to improve the analysis of miRNA regulation in biological pathways. MiTALOS identifies potential pathway regulation by (i) an enrichment analysis of miRNA targets genes and (ii) by using a proximity score to evaluate the functional role of miRNAs in biological pathways by their network proximity. Moreover, miTALOS integrates five different miRNA target prediction tools and two different signaling pathway resources (KEGG and NCI). A graphical visualization of miRNA targets in both KEGG and NCI PID signaling pathways is provided to illustrate their respective pathway context. We perform a functional analysis on prostate cancer-related miRNAs and are able to infer a model of miRNA-mediated regulation on tumor proliferation, mobility and anti-apoptotic behavior. miTALOS provides novel features that accomplish a substantial support to systematically infer regulation of signaling pathways mediated by miRNAs. The web-server is freely accessible at http://hmgu.de/cmb/mitalos.

Dynamic mathematical modeling of IL13-induced signaling in Hodgkin and primary mediastinal B-cell lymphoma allows prediction of therapeutic targets.

Primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of JAK (Janus kinase)/STAT signaling pathway. Because of complex, nonlinear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. We report the development of dynamic pathway models based on quantitative data collected on signaling components of JAK/STAT pathway in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We show that the amounts of STAT5 and STAT6 are higher whereas those of SHP1 are lower in the two lymphoma cell lines than in normal B cells. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In both lymphoma cell lines, we observe interleukin-13 (IL13)-induced activation of IL4 receptor α, JAK2, and STAT5, but not of STAT6. Genome-wide, 11 early and 16 sustained genes are upregulated by IL13 in both lymphoma cell lines. Specifically, the known STAT-inducible negative regulators CISH and SOCS3 are upregulated within 2 hours in MedB-1 but not in L1236 cells. On the basis of this detailed quantitative information, we established two mathematical models, MedB-1 and L1236 model, able to describe the respective experimental data. Most of the model parameters are identifiable and therefore the models are predictive. Sensitivity analysis of the model identifies six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1. We experimentally confirm reduction in target gene expression in response to inhibition of STAT5 phosphorylation, thereby validating one of the predicted targets.

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.

BACKGROUND: External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function. RESULTS: We therefore develop the concept of graph-decorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways in a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the features (e.g. genes) and are thus able to define a graph-delayed correlation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph-decorrelation algorithm (GraDe). To analyze alterations in the gene response in IL-6 stimulated primary mouse hepatocytes, we performed a time-course microarray experiment and applied GraDe. In contrast to standard techniques, the extracted time-resolved gene expression profiles showed that IL-6 activates genes involved in cell cycle progression and cell division. Genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming renders hepatocytes more responsive towards cell proliferation and reduces expenditures for the energy metabolism. CONCLUSIONS: GraDe provides a novel framework for the decomposition of large-scale 'omics' data. We were able to show that including prior knowledge into the separation task leads to a much more structured and detailed separation of the time-dependent responses upon IL-6 stimulation compared to standard methods. A Matlab implementation of the GraDe algorithm is freely available at http://cmb.helmholtz-muenchen.de/grade.

MicroRNA loss enhances learning and memory in mice.

Dicer-dependent noncoding RNAs, including microRNAs (miRNAs), play an important role in a modulation of translation of mRNA transcripts necessary for differentiation in many cell types. In vivo experiments using cell type-specific Dicer1 gene inactivation in neurons showed its essential role for neuronal development and survival. However, little is known about the consequences of a loss of miRNAs in adult, fully differentiated neurons. To address this question, we used an inducible variant of the Cre recombinase (tamoxifen-inducible CreERT2) under control of Camk2a gene regulatory elements. After induction of Dicer1 gene deletion in adult mouse forebrain, we observed a progressive loss of a whole set of brain-specific miRNAs. Animals were tested in a battery of both aversively and appetitively motivated cognitive tasks, such as Morris water maze, IntelliCage system, or trace fear conditioning. Compatible with rather long half-life of miRNAs in hippocampal neurons, we observed an enhancement of memory strength of mutant mice 12 weeks after the Dicer1 gene mutation, before the onset of neurodegenerative process. In acute brain slices, immediately after high-frequency stimulation of the Schaffer collaterals, the efficacy at CA3-to-CA1 synapses was higher in mutant than in control mice, whereas long-term potentiation was comparable between genotypes. This phenotype was reflected at the subcellular and molecular level by the elongated filopodia-like shaped dendritic spines and an increased translation of synaptic plasticity-related proteins, such as BDNF and MMP-9 in mutant animals. The presented work shows miRNAs as key players in the learning and memory process of mammals.

Classification of HER2/neu status in gastric cancer using a breast-cancer derived proteome classifier.

HER2-testing in breast and gastric cancers is mandatory for the treatment with trastuzumab. We hypothesized that imaging mass spectrometry (IMS) of breast cancers may be useful for generating a classifier that may determine HER2-status in other cancer entities irrespective of primary tumor site. A total of 107 breast (n = 48) and gastric (n = 59) cryo tissue samples was analyzed by IMS (HER2 was present in 29 cases). The obtained proteomic profiles were used to create HER2 prediction models using different classification algorithms. A breast cancer proteome derived classifier, with HER2 present in 15 cases, correctly predicted HER2-status in gastric cancers with a sensitivity of 65% and a specificity of 92%. To create a universal classifier for HER2-status, breast and nonbreast cancer samples were combined, which increased sensitivity to 78%, and specificity was 88%. Our proof of principle study provides evidence that HER2-status can be identified on a proteomic level across different cancer types suggesting that HER2 overexpression may constitute a unique molecular event independent of the tumor site. Furthermore, these results indicate that IMS may be useful for the determination of potential drugable targets, as it offers a quicker, cheaper, and more objective analysis than the standard HER2-testing procedures immunohistochemistry and fluorescence in situ hybridization.

Correlated mutations: a hallmark of phenotypic amino acid substitutions.

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/.

Tissue-specific target analysis of disease-associated microRNAs in human signaling pathways.

MicroRNAs are a large class of post-transcriptional regulators that bind to the 3' untranslated region of messenger RNAs. They play a critical role in many cellular processes and have been linked to the control of signal transduction pathways. Recent studies indicate that microRNAs can function as tumor suppressors or even as oncogenes when aberrantly expressed. For more general insights of disease-associated microRNAs, we analyzed their impact on human signaling pathways from two perspectives. On a global scale, we found a core set of signaling pathways with enriched tissue-specific microRNA targets across diseases. The function of these pathways reflects the affinity of microRNAs to regulate cellular processes associated with apoptosis, proliferation or development. Comparing cancer and non-cancer related microRNAs, we found no significant differences between both groups. To unveil the interaction and regulation of microRNAs on signaling pathways locally, we analyzed the cellular location and process type of disease-associated microRNA targets and proteins. While disease-associated proteins are highly enriched in extracellular components of the pathway, microRNA targets are preferentially located in the nucleus. Moreover, targets of disease-associated microRNAs preferentially exhibit an inhibitory effect within the pathways in contrast to disease proteins. Our analysis provides systematic insights into the interaction of disease-associated microRNAs and signaling pathways and uncovers differences in cellular locations and process types of microRNA targets and disease-associated proteins.

PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes.

In recent years, microRNAs have been shown to play important roles in physiological as well as malignant processes. The PhenomiR database http://mips.helmholtz-muenchen.de/phenomir provides data from 542 studies that investigate deregulation of microRNA expression in diseases and biological processes as a systematic, manually curated resource. Using the PhenomiR dataset, we could demonstrate that, depending on disease type, independent information from cell culture studies contrasts with conclusions drawn from patient studies.